Winter 2015

Tag Archives: inflation

Many countries are below replacement fertility levels due to shifting economic status of women and corresponding role shifts for men in taking responsibility for home and child care. Current research shows this is economically harmful but can be both inflationary and deflationary.

Many wealthy nations are considered to be “below replacement fertility” levels. Replacement level is attained when a country’s average birth rate is 2.1 children per woman, 1 per parent with 0.1 to account for infant and child mortality. One popular opinion on the cause of these low and decreased fertility levels is the economic status of women. Economists Bruce Sacerdote and James Feyrer examine three phases of women’s status and the fertility levels correlated with each phase. In the low-female-status phase, women have very limited if any economic role outside of the home. Fertility in this case is high. In the middle phase, women have roles and responsibilities outside the home yet they are still left with the burden of all home and child care. Fertility is lowest in countries such as Japan, Spain and Italy who find themselves in this phase. In a third phase, women still have opportunity to pursue roles outside the home AND their male counterparts pitch in with maintaining the home and childcare. Fertility is much higher here than in the middle phase.

Sacerdote and Feyrer examine other aspects which impact families’ fertility choices. It is interesting to think that in high-income countries, families make fertility decisions with peer effects in mind. Then in turn, societies with more children may develop more family-supporting infrastructure (e.g. tax incentives, increased maternity leave, and day care subsidies for families with children in France). The multiplier effect of social policy that this leads to is interesting. To think that social policy that supports families could influence one family that could influence many others through the peer effect social multiplier is an interesting concept.

Korea, Singapore & Hong Kong’s fertility levels have decreased from 3.5 to 6.0 children per woman in 1970 to below 1.5 children per woman in 2005. Specifically, Hong Kong’s fertility rate is the lowest in the world at 1.0 children per woman. I find this interesting because I would like to know more about how China’s one-child policy has affected this rate. The article says China’s fertility level is near replacement overall but I wonder how / how quickly this has come to be since the one-child policy was abolished in 2013.

Fertility rates can be difficult to predict for recent years and impossible to predict in real time. The data is difficult to collect and there are multiple ways to collect it. Japan in particular has had a difficult time measuring fertility rates but now that they have, they realize that in 2014, Japan’s birth rate shrunk by the highest amount on record. Their predicted fertility rates have been way off and overestimated consistently since 1965. Ana Swanson writes for the Washington Post:

“A working paper from Tokyo’s Waseda University… argues that the effects of an aging population on deflation are more complicated than typically thought – that aging is deflationary when caused by an increase in longevity but inflationary when caused by a decline in birth rate. Overall, Japan’s aging population generated deflation of 0.6 percentage points annually over the past 40 years, the authors say.”

Thesis: On the optimal response for monetary policy when on the ZLB, fiscal policy is constrained in boosting aggregate demand, because of the Fed’s 2% inflation target, and thus in order to for it to work effectively, it would require a ‘regime shift’ to price level targeting.

Summer closing nearer, labor market conditions improving, household purchasing power has increased due to the decline in commodity prices, it won’t be long before interest rates are on the rise and the ZLB becomes a thing of the past, at least for America. David Beckworth seems to agree that as the U.S economy improves, the ZLB debate will become moot. Nonetheless, it is important to keep the ZLB debate in mind, since we still don’t have a consensus amongst economists for the best way to conduct monetary policy at the ZLB. David Beckworth write’s in response to Ben Bernanke on the future of Monetary policy, where Bernanke suggests:

A possible direction of change for the monetary policy framework would be to keep the targets-based approach that I favor, but to change the target. Suggestions that have been made include raising the inflation target, targeting the price level, or targeting some function of nominal GDP… a principal motivation that proponents offer for changing the monetary policy target is to deal more effectively with the zero lower bound on interest rates. But economically, it would be preferable to have more proactive fiscal policies and a more balanced monetary-fiscal mix when interest rates are close to zero. Greater reliance on fiscal policy would probably give better results, and would certainly be easier to explain, than changing the target for monetary policy.

Bernanke takes a stance that a monetary-fiscal mix would’ve been preferable in generating greater aggregate demand over the past six years. However Beckworth argues that fiscal policy is limited by its ability to boost aggregate demand, because of the Fed’s 2% target inflation rate. This is interesting because part of Bernanke’s blog post, suggests that tinkering with the 2% inflation target for future monetary policy would be costly, mainly because monetary policy since the Great Moderation has anchored inflation expectations at 2%, thus changing the level of inflation target would take time in establishing long-term credibility in order to deviate from the history we have had with 2% inflation targeting. Although Bernanke suggests that the monetary-fiscal mix would be optimal, he acknowledges that “the probability of getting Congress to accept larger automatic stabilizers.. is low.”

Beckworth demonstrates with an example, that for fiscal policy to have worked in reducing the output gap over the past 6 years, we would’ve needed a monetary policy ‘regime shift’ to price level targeting. In his example, the regime shift would require the price level target to bring back the PCE to its pre-crisis trend path. In order to bring the PCE back to trend, this would require temporary high periods of inflation. This inflation burst “would be the catalyst that spurred robust aggregate demand growth.”
Further in the example we assume the Fed has made QE2 conditional on the PCE returning to its 2002-2008 trend path. In the graph below, we see three different paths for the price level target which are highlighted as three rates for catch-up inflation, 3%, 4%, and a 5%. We see that greater levels of inflation reduce the amount of time it takes to catch up to the previous PCE trend.

So in order to get robust aggregate demand growth there needs to be a temporary period of higher inflation. However with the Fed’s 2% inflation target, this would be infeasible, hence rendering fiscal policy ineffective if it is only able to benefit the economy upon reaching the 2% cap on inflation. This topic is good for discussion because it is an example of why fiscal policy may not be very effective during times of economic turmoil. We see the downsides of anchoring inflation at 2% since we limit the alternative methods for a robust recovery, but although probably unlikely, a regime shift could have resulted in robust recovery during the great recession.

meThesis: Consumers with higher education and income can predict next year’s inflation rate better than their counterparts, i.e. the average consumer.

On last week’s blog post, in an effort to match up Michigan’s survey of inflation expectations, the Survey of Professional Forecasters (SPF), and a RW no-change forecast, all forecasting one-year ahead, I was unable to conclude beyond a reasonable doubt which forecast model would be the best for predicting inflation, but in this post I hope to redeem myself.

As we consider a consumer’s level of income and education, what should we expect to happen to their predictive power? Some intuition would tell us that as a consumer’s level of income rises, she may have a higher propensity to save, because she will have more excess funds. Naturally, she may invest these funds, and hold a portfolio comprised of stocks, bonds, and other securities, in order to grow her nest egg for retirement, or set money aside to cushion against economic downturns. Thus it would be important for her to frequently keep track of the inflation rate, to make sure that her investment is not eroded by price increases.

Given education, it is plausible that higher education on average leads to higher income for the consumer, which goes back to our previous argument on income. However we can also infer that more educated consumers are more likely to read the newspaper and be more informed about fluctuations in the inflation rate, a claim made by Christopher Carrol. Lastly it may be the case that more educated consumers are simply more likely to know what inflation is in the first place, as opposed to their counterparts. To test this claim, we can sum up the number of survey participants according to their income group, from the Michigan Survey, who did not know what to say when asked about their inflation expectation. We see there is evidence that indeed people with lower education were not able to provide an answer more frequently than individuals with a graduate degree. This is looking at the far ends of the education spectrum, but the relationship holds nonetheless, as we increase education, people less frequently fail to give an answer for their inflation prediction. Interestingly it seems that consumers with less than a high school education know less, on average, about inflation now than they did back in the 80s.

My claims above would have no ‘oomph’ to them if I didn’t back them up with any evidence. So are we right in assuming that higher education and income lead to better inflation predictions? The answer is a resounding yes!
Let’s take different education and income subgroups, using the Michigan Survey one more time, and lets take the median inflation expectation at each quarter for each subgroup. We use Median, because, this measure is more robust against outliers. (Note choosing mean expectation gives weaker results, in that I am able to statistically reject more often). Finally lets compare each subgroup against one another and see how well they do in comparison at predicting the median-CPI in our experiment. (Reason for this specific inflation measure is explained on last week’s blog). I also use the same Diebold-Mariano test used on my previous post, to test for statistical significance of predictive superiority amongst subgroups. The time period I analyze is 1982-2014, because 1981Q3 is when the SPF began.

So let’s look at the results! Below I report values for income, as the probability that the highest income group performs better than the alternative income groups. Likewise for education, I display the probability that those with graduate level education do better than their counterparts. Finally we put the highest education and income groups against the SPF, and settle the forecasting battle once and for all. In all of the following results, we should interpret them as probabilities in repeated trials.

Note: These are actually p-values, but I report them this way to make the results more intuitive.

The above table demonstrates that survey participants grouped in the top 25% bracket, consistently beat their counterparts with about 99% probability. However when the predictions of the top income group were tested against those from the SPF, there was only a 34.31% probability that the high income group would predict better. Similarly, there is large evidence that the group with graduate school education beats every other education group’s predictions with a 99% probability, except for those with a college Bachelor’s degree, but still beating them with a 92.08% probability. The high education group also lost miserably to the SPF, with a probably of fairing better than the SPF of 27.69%. We get very similar, statistically significant results, when we compare the alternative income groups against a lower levels of income and education against the lowest income and education levels. From this we gain two conclusions:

1. As income and education increase, predictive ability for inflation increases unambiguously.
2. There is no subgroup from the Michigan survey that can predict the inflation better than the SPF, at least to a statistically significant level like.

Here is a graph comparing graduate level education vs less than high school, and the top 25% income group against the bottom 25% (For those more visually inclined 🙂 ) What we see is that the results are consistent with those in the table above. One thing to note is that inflation expectations for low education and income groups are higher than their counterparts for most of the time period analyzed (1982-2014).

One final note, I find out conclusively that the SPF does better than any income group, except the Top 25%, although the SPF probably does better, we cannot tell beyond a reasonable doubt. This result would satisfy the claim in the beginning of the post that those with higher incomes may have a higher predisposition to know the inflation rate, because it is only those in the top 25% income bracket that are able to make predictions somewhat as close to the SPF’s. This claim would be consistent with the fact that about half of Americans hold any assets, hence only individuals in the highest income groups would have any interest in the inflation rate.

Thesis: Fed should be more patient to increase the federal funds rate because still inflation is not sufficient to boost the economy and the unemployment rate is higher than the boom cycle.

Fed have implicated that it would increase the short-term interest rate by midyear between June and September since January. Janet Yellen, Federal Reserve Chairwoman, gives a speech in front of economists in San Francisco, delivering that she is cautiously optimistic the economy is approaching the point where it doesn’t need the near-zero interest rates to make an expansion (Wall Street Journal). However, she emphasizes that the pace should be gradual, illustrating that it would move in small steps with enough caution to avoid undermining the economic expansion. Furthermore, Wall Street Journal explains what would make Fed halt the plan to begin raising interest rate. “In short, Ms. Yellen wants to be sure that inflation isn’t going to fall any further. It has been running below the Fed’s 2% goal for nearly three straight years. She says it is necessary to care about wage growth, core consumer prices, and other indicators of underlying inflation pressures before Fed increase the federal funds rate.

I extract two graphs from St. Louis Fed’s FRED online tool, describing consumer price index in different time period. The first graph shows the general trend of consumer price index from 2008 to 2015 while the second graph illustrates some details between 2014 and 2015. Since consumer price index is related to the inflation (inflation is defined as a process of continuously rising prices), it is clear that Fed should worry about falling inflation problem since CPI is falling in 2015. Inflation can be an important measurement for boosting the economy, so Fed care about keeping the constant inflation. The problem is, if Fed increase the federal funds rate, the market will react as the inflation will fall down.

I also generate the unemployment rate graph from St. Louis Fed’s FRED online tool to figure out the average unemployment rate of the U.S. According to Federal Reserve Bank of San Francisco website, the natural unemployment rate is around 5% while the current unemployment rate is about 5.5%.

Increasing the interest rate can impact on the unemployment rate, which is not fully recovered. For example, the graph above shows the unemployment rate of 2006 and 2008, much lower than that of today. I think increasing the interest rate is risky in that sense. In addition, although the unemployment rate becomes lower and lower, there are numerous factors that we should consider before we assume that the number is correct. For example, many experts argue that the definition of the unemployment is not sufficient because it is subjective in terms of “willingness” and “active job search.” Also, Fortune points out the “aging population” affect on the unemployment rate because many baby-boomers are retiring now. Therefore, I believe Fed should be more patient to increase its funds rate because of low inflation and not sufficient unemployment rate.

The gap between market forecasts of inflation and where inflation will likely go may be a feature, not a bug. This gap is a risk premia that can be informative about what scenarios are worrisome to investors, and as such may be useful for policy makers deciding on how to weight the relative costs of inflation and deflation.

Justin Wolfers’ recent recent NYT article on inflation expectations sets the stage. In this article, he walks through an academic asset pricing paper that estimates a probability distribution for future inflation based on the prices of bets on inflation. The basic idea is that there is a betting market in which people can place bets on where they think inflation will be going. Just like how a bookie’s prices say something about the probability of certain horses winning a race, the prices on this betting market (otherwise known as a derivatives market) make statements about the probability inflation ends up in certain zones. Justin summarizes the findings:

While traders view inflation of roughly 2 percent as the most likely outcome, the market is also telling us the probability of other levels of inflation — or deflation. And it is saying that the risks of missing the 2 percent target are extremely unbalanced: It is twice as likely that inflation will come in below the Fed’s target as above it.

But there’s another aspect to asset prices that isn’t as important for horse races: risk premia. Whether inflation is high or not is related to the strength of the jobs market and the economy as a whole. In particular, if I were to tell you that there was going to be deflation in two years, your best prediction would be that we were going through a double dip recession in which aggregate demand fell. This is clearly bad, and as such you would be willing to buy insurance against this scenario. In the language of horse betting, you would be willing to pay better than fair odds that there will be deflation. Sure you might lose money on average, but when deflation hits and you lose your job, at least you got your racetrack winnings to cushion the blow.

As such, the market forecast is equal to the true future expected inflation plus a risk premium that reflects whether low inflation or high inflation scenarios are scarier. If people are scared of a Japan style deflation, then the market forecast will underestimate true inflation. If on the other hand people are worried about 1970’s style stagflation, the market forecast will overestimate true inflation.

While this can be a nuisance if you want to get the “best” physical forecast of actual inflation, it can actually be tremendously valuable for policy makers who need to decide on whether to be more worried about the costs of high inflation or low inflation scenarios. Sure, if you’re playing a game and trying to minimize your prediction error the market forecast might not be helpful. But this can be very useful for policy! Negative risk premia on inflation expectations tell policy makers that low inflation scenarios are much worse than high inflation scenarios. If this is the case, then the inflation target has reason to be asymmetric — better to avoid scary deflation than deal with temporarily higher inflation.

As a more general point, this risk premia analysis shows how asset pricing is in some ways a form of quantitative psychology. Estimating risk premia can be interpreted as answering the question “based on these asset returns, what does that say about the kind of events that scare people”? And once policy makers know about these feared scenarios, they can adjust policy to make sure they do not come to be.

Nowadays, the Fed faces with the severe dilemma between low inflation and job gains. The unemployment rate has fallen to 5.7% from 6.6% a year ago and 8% two years ago while the inflation rate is still below the target 2% rate. According to Wall Street Journal, the stronger job market provides reason of raising short-term interest rates to prevent the overheating market while low wage growth and inflation show the signal that overheating problem wouldn’t be in the near future.

Officially, the Fed already said a high possibility of raising short-term interest rate around the midyear. However, many Fed officials worry about the market situation although net hiring increases during the November-to-January by more than 1 million. Their worries come from the inflation which is still below the Fed’s 2% objective and little wage growth. Why does low inflation matter? It is a simple economic theory called Phillips curve. Basically, it is a historic inverse relationship between unemployment rates and inflation rates in the economy. In theory, there is a point where the long-run Phillips curve meets the short-run Phillips curve, where the Fed and other governments target on.

“Economists call this cutoff point a non-accelerating inflation rate of unemployment, or Nairu, and also point to a “natural rate” of unemployment where inflation is stable in the longer-run. The problem is nobody knows the cutoff point. Economists merely estimate it” (Wall Street Journal). Because of uncertainty in estimating the point, it is hard to set the interest rate at the right time. Both Fed officials and policy makers want to see the obvious sign to make sure that the economy is close to the full employment, but not as much as to the overheating point.

There are two options for Fed; it can be patient until the market shows a clearer sign or take an action by increasing short-term interest rate. Personally, I am in the position that Fed should wait because I think raising the interest rate is too risky. As Rosengren said, “Low level of inflation in most developed economies meant the U.S. central bank shouldn’t hurry to raise interest rates.” Furthermore, still the economic measures are not fully recovered as before the sub-prime mortgage. For example, many people point out involuntarily part-time workers, which make “job gains” doubtful. “There are still almost 7 million workers counted as employed who say they are working part-time involuntarily” (Wall Street Journal). Fed should be more careful about its increasing interest rate unless the whole economy falls into the deep recession again.